Hive的导入导出方式汇总

导入

1. 本地文件导入到Hive表CREATE TABLE testA (  

       id INT,  
       name string,  
       area string  
   ) PARTITIONED BY (create_time string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘,‘ STORED AS TEXTFILE;  
   
   CREATE TABLE testB (  
       id INT,  
       name string,  
       area string,  
       code string  
   ) PARTITIONED BY (create_time string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘,‘ STORED AS TEXTFILE; 
   
   // 数据文件（sourceA.txt）：
   
   1,fish1,SZ  
   2,fish2,SH  
   3,fish3,HZ  
   4,fish4,QD  
   5,fish5,SR 
   
   // 数据文件（sourceB.txt）：
   1,zy1,SZ,1001  
   2,zy2,SH,1002  
   3,zy3,HZ,1003  
   4,zy4,QD,1004  
   5,zy5,SR,1005 
   
   // 方式一：load进数据
   hive> load data local inpath ‘/tmp/20210504/sourceA.txt‘ into table testA partition(create_time=‘2021-05-04‘);
   Loading data to table one.testa partition (create_time=2021-05-04)
   OK
   Time taken: 1.552 seconds
   
   
   hive> load data local inpath ‘/tmp/20210504/sourceB.txt‘ into table testB partition(create_time=‘2021-05-04‘);
   Loading data to table one.testb partition (create_time=2021-05-04)
   OK
   Time taken: 0.789 seconds
   
    hive> select * from testA;
   OK
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04
   Time taken: 2.227 seconds, Fetched: 5 row(s)
   hive> select * from testB;
   OK
   1    zy1    SZ    1001    2021-05-04
   2    zy2    SH    1002    2021-05-04
   3    zy3    HZ    1003    2021-05-04
   4    zy4    QD    1004    2021-05-04
   5    zy5    SR    1005    2021-05-04
   Time taken: 0.175 seconds, Fetched: 5 row(s)
   
   
   // 方式二 insert
   
   
   
   删除表数据
   hive> truncate table testA;
   OK
   Time taken: 0.326 seconds
   
   删除分区：
   hive> alter table testB drop partition(create_time = ‘2021-05-04‘);
   Dropped the partition create_time=2021-05-04
   OK
   Time taken: 0.27 seconds
   
   hive不能删除行
   如果想删除部分数据，就创建临时表 ，把留下的数据查出来 插入进去

    

    

    

2. Hive表导入到Hive表
   

   insert into table testA partition(create_time=‘2021-05-06‘) select id, name, area  from testB where id = 1;
   有MR
   Time taken: 173.64 seconds
   
   hive> SELECT * FROM testA;
   OK
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04
   1    zy1    SZ    2021-05-06
   1    zy1    SZ    2021-05-06
   Time taken: 0.246 seconds, Fetched: 7 row(s)
   
   
   INSERT INTO TABLE testA PARTITION(create_time) select id, name, area, code from testB where id = 2;
   hive> select * from testA;
   OK
   2    zy2    SH    1002
   2    zy2    SH    1002
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04
   1    zy1    SZ    2021-05-06
   1    zy1    SZ    2021-05-06
   Time taken: 0.212 seconds, Fetched: 9 row(s)
   
   
   1，将testB中id=1的行，导入到testA，分区为2021-05-06
   
   2，将testB中id=2的行，导入到testA，分区create_time为id=2行的code值。

    

3. HDFS文件导入到Hive表
   

   HDFS文件导入到Hive表
   hdfs dfs -put /tmp/20210504/sourceA.txt /xiaoke003/sourceA
   hive> load data inpath ‘/xiaoke002/sourceA‘ into table testA partition(create_time= ‘2021-05-04‘);
   Loading data to table one.testa partition (create_time=2021-05-04)
   OK
   Time taken: 0.54 seconds
   hive> SELECT * FROM testA;
   OK
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04
   Time taken: 0.122 seconds, Fetched: 5 row(s)

    

4. 创建表的过程中从其他表导入
   

   create table testC as select name, code from testB;

    

5. 通过sqoop将mysql库导入到Hive表

导出

1. Hive表导出到本地文件系统
   

   insert overwrite local directory ‘/tmp/20210504/output/one‘ row format delimited fields terminated by ‘,‘ select * from testA;
   
   通过INSERT OVERWRITE LOCAL DIRECTORY将hive表testA数据导入到/tmp/20210504/output/one/000000_0，众所周知，HQL会启动Mapreduce完成，
   /tmp/20210504/output/one就是Mapreduce输出路径，产生的结果存放在文件名为：000000_0。

    

2. Hive表导出到HDFS
   

   insert overwrite directory ‘/tmp/xiaoke002/one‘ row format delimited fields terminated by ‘,‘ select * from testA;
   
   
   [root@ke03 output]# hdfs dfs -cat /xiaoke002/one/000000_0
   1fish1SZ2021-05-04
   2fish2SH2021-05-04
   3fish3HZ2021-05-04
   4fish4QD2021-05-04
   5fish5SR2021-05-04

    

3. 使用-e -f 参数来导出数据
   

   -e 的使用方式，后面接SQL语句。>>后面为输出文件路径
   hive -e "use one;select * from testA" >> ./two
   
   
   
   -f 的使用方式，后面接存放sql语句的文件。>>后面为输出文件路径
   [root@ke03 output]# cat sql.sql 
   use one; select * from testA;
   
   hive -f sql.sql  >> three.txt
   
   
   
   [root@ke03 output]# cat two 
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04
   
   [root@ke03 output]# cat three.txt 
   1    fish1    SZ    2021-05-04
   2    fish2    SH    2021-05-04
   3    fish3    HZ    2021-05-04
   4    fish4    QD    2021-05-04
   5    fish5    SR    2021-05-04

    

4. 从hdfs中直接导出
   

   hdfs dfs -get /xiaoke002/one/000000_0 ./four
   
   vi four
   1^Afish1^ASZ^A2021-05-04
   2^Afish2^ASH^A2021-05-04
   3^Afish3^AHZ^A2021-05-04
   4^Afish4^AQD^A2021-05-04
   5^Afish5^ASR^A2021-05-04

    

5. 通过sqoop将Hive表导出到mysql库

Hive的导入导出方式汇总

原文：https://www.cnblogs.com/bigdata-familyMeals/p/14730226.html